


import copy
from typing import Dict, Optional

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig


lowerCAmelCase			=				{
    'facebook/maskformer-swin-base-ade': (
        'https://huggingface.co/facebook/maskformer-swin-base-ade/blob/main/config.json'
    )
    # See all MaskFormer models at https://huggingface.co/models?filter=maskformer
}

lowerCAmelCase			=				logging.get_logger(__name__)


class 			_a				(     UpperCamelCase__     ):
							_lowercase      :     Optional[int]     =					'''maskformer'''
							_lowercase      :     Any     =					{'''hidden_size''': '''mask_feature_size'''}
							_lowercase      :     int     =					['''resnet''', '''swin''']
							_lowercase      :     int     =					['''detr''']

							def __init__(				self:      Dict       ,		UpperCamelCase_:      int = 256       ,		UpperCamelCase_:      int = 256       ,		UpperCamelCase_:      float = 0.1       ,		UpperCamelCase_:      bool = False       ,		UpperCamelCase_:      Optional[Dict] = None       ,		UpperCamelCase_:      Optional[Dict] = None       ,		UpperCamelCase_:      float = 0.02       ,		UpperCamelCase_:      float = 1.0       ,		UpperCamelCase_:      float = 1.0       ,		UpperCamelCase_:      float = 1.0       ,		UpperCamelCase_:      float = 20.0       ,		UpperCamelCase_:      Optional[bool] = None       ,		**UpperCamelCase_:      int       ,		)     ->  Optional[int]:





									"""simple docstring"""







									if backbone_config is None:
											# fall back to https://huggingface.co/microsoft/swin-base-patch4-window12-384-in22k
											lowercase__				= SwinConfig(
											    image_size=384       ,		in_channels=3       ,		patch_size=4       ,		embed_dim=128       ,		depths=[2, 2, 18, 2]       ,		num_heads=[4, 8, 16, 32]       ,		window_size=12       ,		drop_path_rate=0.3       ,		out_features=['''stage1''', '''stage2''', '''stage3''', '''stage4''']       ,		)

									if isinstance(UpperCamelCase_       ,		UpperCamelCase_				):
											lowercase__				= backbone_config.pop('''model_type'''				)
											lowercase__				= CONFIG_MAPPING[backbone_model_type]
											lowercase__				= config_class.from_dict(UpperCamelCase_				)

									# verify that the backbone is supported
									if backbone_config.model_type not in self.backbones_supported:
											logger.warning_once(
											    f'Backbone {backbone_config.model_type} is not a supported model and may not be compatible with MaskFormer. '
											    f'Supported model types: {",".join(self.backbones_supported				)}'				)

									if decoder_config is None:
											# fall back to https://huggingface.co/facebook/detr-resnet-50
											lowercase__				= DetrConfig()
									else:
											# verify that the decoder is supported
											lowercase__				= (
											    decoder_config.pop('''model_type'''				) if isinstance(UpperCamelCase_       ,		UpperCamelCase_				) else decoder_config.model_type
											)
											if decoder_type not in self.decoders_supported:
													raise ValueError(
													    f'Transformer Decoder {decoder_type} not supported, please use one of'
													    f' {",".join(self.decoders_supported				)}'				)
											if isinstance(UpperCamelCase_       ,		UpperCamelCase_				):
													lowercase__				= CONFIG_MAPPING[decoder_type]
													lowercase__				= config_class.from_dict(UpperCamelCase_				)

									lowercase__				= backbone_config
									lowercase__				= decoder_config
									# main feature dimension for the model
									lowercase__				= fpn_feature_size
									lowercase__				= mask_feature_size
									# initializer
									lowercase__				= init_std
									lowercase__				= init_xavier_std
									# Hungarian matcher && loss
									lowercase__				= cross_entropy_weight
									lowercase__				= dice_weight
									lowercase__				= mask_weight
									lowercase__				= use_auxiliary_loss
									lowercase__				= no_object_weight
									lowercase__				= output_auxiliary_logits

									lowercase__				= self.decoder_config.encoder_attention_heads
									lowercase__				= self.decoder_config.num_hidden_layers
									super().__init__(**UpperCamelCase_				)

							@classmethod
							def  lowerCamelCase_					(				cls:      Tuple       ,		UpperCamelCase_:      PretrainedConfig       ,		UpperCamelCase_:      PretrainedConfig       ,		**UpperCamelCase_:      Any				)     ->  str:





									"""simple docstring"""







									return cls(
									    backbone_config=UpperCamelCase_       ,		decoder_config=UpperCamelCase_       ,		**UpperCamelCase_       ,		)


							def  lowerCamelCase_					(				self:      Union[str, Any]				)     ->  Dict[str, any]:





									"""simple docstring"""







									lowercase__				= copy.deepcopy(self.__dict__				)
									lowercase__				= self.backbone_config.to_dict()
									lowercase__				= self.decoder_config.to_dict()
									lowercase__				= self.__class__.model_type
									return output









"""simple docstring"""





import logging
import os

from .state import PartialState

class 						lowercase   (   logging.LoggerAdapter   ):





      @staticmethod
      def        _snake_case     (			lowercase					)						->	Optional[Any]:
            lowerCAmelCase    		=			PartialState()
            return not main_process_only or (main_process_only and state.is_main_process)





      def        _snake_case     (			self ,		lowercase ,		lowercase ,		*lowercase ,		**lowercase					)						->	Dict:
            if PartialState._shared_state == {}:
                  raise RuntimeError(
                      """You must initialize the accelerate state by calling either `PartialState()` or `Accelerator()` before using the logging utility."""					)
            lowerCAmelCase    		=			kwargs.pop("""main_process_only""" ,		lowercase					)
            lowerCAmelCase    		=			kwargs.pop("""in_order""" ,		lowercase					)

            if self.isEnabledFor(lowercase					):
                  if self._should_log(lowercase					):
                        lowerCAmelCase		,						lowerCAmelCase    		=			self.process(lowercase ,		lowercase					)
                        self.logger.log(lowercase ,		lowercase ,		*lowercase ,		**lowercase					)

                  elif in_order:
                        lowerCAmelCase    		=			PartialState()
                        for i in range(state.num_processes					):
                              if i == state.process_index:
                                    lowerCAmelCase		,						lowerCAmelCase    		=			self.process(lowercase ,		lowercase					)
                                    self.logger.log(lowercase ,		lowercase ,		*lowercase ,		**lowercase					)
                              state.wait_for_everyone()







def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		str				,		SCREAMING_SNAKE_CASE	:		str = None     ):







      '''simple docstring'''




      if log_level is None:
            lowerCAmelCase    		=			os.environ.get("""ACCELERATE_LOG_LEVEL"""				,		SCREAMING_SNAKE_CASE     )
      lowerCAmelCase    		=			logging.getLogger(SCREAMING_SNAKE_CASE     )
      if log_level is not None:
            logger.setLevel(log_level.upper()     )
            logger.root.setLevel(log_level.upper()     )
      return MultiProcessAdapter(SCREAMING_SNAKE_CASE				,		{}     )






